These templates cover the main analytics steps and allow continuous improvement and integration.
| Type of Analysis | Skills and Tools |
|---|---|
| Gene expression analysis | RNA-seq, STAR, DESeq, Snakemake, R, Python Workflow |
| Gene enrichment analysis | RNA-seq, STAR, DESeq, Snakemake, R, Python Workflow |
| Variant calling analysis | BWA, Snakemake, Workflow |
| Genome wide association study | kGWASflow, Workflow |
| Single Cell Analysis | scRNASeq, Scanpy, Python, Jupyter Notebook Workflow |
| Amplicon data analysis (16S) | Mothur, QIIME2, R, Python Workflow: In progress |
| Metagenomics data analysis Microbial and pathway profiling |
Biobakery, R, Python Workflow: In progress |
| Microbiome Machine learning models | MikropML, Caret, Snakemake, R, Python Workflow |
| Gene Ontology Enrichment | GO, Proteomics, Snakemake, R, Python Workflow |
| Model | Tools |
|---|---|
| Logistic Regression | MikropML, Caret, Snakemake, R, Python Workflow: In progress |
| Rainfall forest | Snakemake, R, Python Workflow: In progress |
| Support vector machine | Snakemake, R, Python Workflow: In progress |
| Analysis | Tools |
|---|---|
| Precipitation & drought | Snakemake, R, Python Workflow: In progress |
| Temperature anomalies | Snakemake, R, Python Workflow: In progress |
| Time Series Analysis | R, Python Workflow: In progress |
Reference: https://f1000research.com/articles/10-33
Aspects to
consider for sustainable data analysis.

Daily global drought index (Standardized z-scores for ~50years).
Temperature anomalies from 1880 (inner layer) to present (2022, outer layer).
